Statistical Optimum Design of Heat Exchangers

The optimal design of a heat exchanger system is based on given model parameters together with given standard ranges for machine design variables. The goals set for minimizing the Life Cycle Cost (LCC) function which represents the price of the saved energy, for maximizing the momentary heat recovery output with given constraints satisfied and taking into account the uncertainty in the models were successfully done. Nondominated Sorting Genetic Algorithm II (NSGA-II) for the design optimization of a system is presented and implemented inMatlab environment. Markov ChainMonte Carlo (MCMC) methods are also used to take into account the uncertainty in themodels. Results show that the price of saved energy can be optimized. A wet heat exchanger is found to be more efficient and beneficial than a dry heat exchanger even though its construction is expensive (160 EUR/m2) compared to the construction of a dry heat exchanger (50 EUR/m2). It has been found that the longer lifetime weights higher CAPEX and lower OPEX and vice versa, and the effect of the uncertainty in the models has been identified in a simplified case of minimizing the area of a dry heat exchanger.

Identifying strategies for mitigating the global warming impact of the EU-25 economy using a multi-objective input-output approach

Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.

Comparación de la capacidad predictiva de los modelos de coeficientes fijos frente a variables en los modelos econométricos regionales: un análisis para Cataluña

Durante las últimas décadas se ha producido un creciente interés en nuestro país en relación a las economías regionales dada la necesidad de los gobiernos regionales de obtener información sobre sus economías para así llevar a cabo actuaciones de política económica más efectivas y eficientes. En este marco, los modelos econométricos constituyen una herramienta de utilidad puesto que ofrecen información sobre las relaciones estructurales que se dan en una economía y permiten predecir su evolución. Sin embargo, la utilización de dichos modelos con finalidad predictiva se enfrenta al inconveniente de la elevada inestabilidad a corto plazo que se produce en las relaciones entre variables económicas a nivel regional. Por este motivo, en el presente trabajo se propone la utilización de un modelo de coeficientes variables para recoger dicha inestabilidad y mejorar las predicciones sobre la evolución de las variables del bloque de producción de la economía catalana. Para contrastar la mejora obtenida a partir de la aplicación de dicho modelo, se compara su capacidad predictiva con la de un modelo de coeficientes fijos. Los resultados muestran un mejor comportamiento del modelo de coeficientes variables frente al modelo de coeficientes fijos.

Revisió de la recerca educativa sobre les variables explicatives del rendiment acadèmic:Apunts per a l'ús del criteri de "modificabilitat pedagògica" de les variables.

La conceptualització del concepte de rendiment acadèmic ha variat al llarg de lahistòria des de definicions que es basaven en un únic criteri fins a les més actuals concepcionsmultidimensionals. Aquestes darreres apareixen com a resultat del desenvolupamentd'aquest concepte, paral.lel a l'evolució històrica d'un fenomen més ampli:el fracàs escolar

Prevalencia de la sintomatología del Síndrome de Asperger y variables asociadas en preescolares españoles

Asperger’s Syndrome (AS) forms part of the whole spectrum of autistic disorders. Until recently it has not been studied in early ages. The aim of this study is to determine the AS’s prevalence of symptoms in general preschool, rural and urban population. In addition, the association of the development areas and symptoms of anxiety and the presence of symptoms of AS was analized. The sample ofthis study consisted in 1104 preschool children between 3-6 years old. The presence of AS’s symptoms was evaluated by a screening tool for psychiatric disorders. This tool was applied to both, preschooler’s parents and their teachers The prevalence of symptoms of AS for parents and teachers was 11.7‰ and 8.1‰, respectively. The presence of AS’s symptoms was associated with language compression delays, general and fine motor coordination, self-help skills and impairment in game activities. In addition, our results showed that the AS has a strong association with specific phobia symptoms and tics. We conclude that an early detection of AS’s symptoms is possible since we found similar prevalence described in other recent researches. Given the impairment associated with AS, its detection is highly recommended

Variables cognitivas y metacognitivas en la resolución de problemas de química: propuesta de estrategias didácticas

This paper presents and classifies the cognitive and metacognitive variables involved in the processes that students execute in problem solving. Moreover, it shows how these variables affect the students success in problem solving. These variables are classified in: piagetian and neo-piagetian, representational, metacognitive and transfer of learning. In the first group of variables it is discussed formal reasoning ability and other neo-piagetian factors. In the second group of variables it is analysed mental models and external representations. Implications for chemistry education are collected as a proposal of didactic strategies in the classroom.

Least squares regression with errors in both variables: case studies

Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.

Influencia de variables de formulación en la viscosidad de emulsiones de surfactante aniónico-aceite-agua

Phase transition and viscosity behavior of emulsified systems were studied after modifying their physicochemical formulation. Effects of concentration and nature of salts and n-alcohols, and water/oil relation on the rheological properties of emulsions were also studied. Pre-equilibrated systems were emulsified according to an agitation procedure, and the viscosity (cP) was measured at different shear rates ranging from 1 to 300 s-1. The phase behavior, as well as the emulsion type based on electrolytic conductivity, was observed. Several interpretations of the flow and viscosity curves of emulsions were made through the estimation of rheological parameters such as consistency index "k" and behavior index "n".

Towards input/output-free modelling of linear infinite-dimensional systems in continuous time

This dissertation describes a networking approach to infinite-dimensional systems theory, where there is a minimal distinction between inputs and outputs. We introduce and study two closely related classes of systems, namely the state/signal systems and the port-Hamiltonian systems, and describe how they relate to each other. Some basic theory for these two classes of systems and the interconnections of such systems is provided. The main emphasis lies on passive and conservative systems, and the theoretical concepts are illustrated using the example of a lossless transfer line. Much remains to be done in this field and we point to some directions for future studies as well.

Incubation period of Hemileia vastatrix in coffee plants in Brazil simulated under climate change

Risk analysis of climate change on plant diseases has great importance for agriculture since it allows the evaluation of management strategies to minimize future damages. This work aimed to simulate future scenarios of coffee rust (Hemileia vastatrix) epidemics by elaborating geographic distribution maps using a model that estimates the pathogen incubation period and the output from three General Circulation Models (CSIRO-Mk3.0, INM-CM3.0, and MIROC3.2.medres). The climatological normal from 1961-1990 was compared with that of the decades 2020s, 2050s and 2080s using scenarios A2 and B1 from the IPCC. Maps were prepared with a spatial resolution of 0.5 × 0.5 degrees of latitude and longitude for ten producing states in Brazil. The climate variables used were maximum and minimum monthly temperatures. The maps obtained in scenario A2 showed a tendency towards a reduction in the incubation period when future scenarios are compared with the climatological normal from 1961-1990. A reduction in the period was also observed in scenario B1, although smaller than that in scenario A2.

Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

RELATIONSHIP BETWEEN CLIMATE VARIABLES, TRUNK GROWTH RATE AND WOOD DENSITY OF Eucalyptus grandis W. Mill ex Maiden TREES

ABSTRACT Climatic conditions stimulates the cambial activity of plants, and cause significant changes in trunk diameter growth and wood characteristics. The objective of this study was to evaluate the influence of climate variables in the diameter growth rate of the stem and the wood density of Eucalyptus grandis trees in different classes of the basal area. A total of 25 Eucalyptus trees at 22 months of age were selected according to the basal area distribution. Dendrometer bands were installed at the height of 1.30 meters (DBH) to monitor the diameter growth every 14 days, for 26 months. After measuring growth, the trees were felled and wood discs were removed at the DBH level to determine the radial density profile through x-ray microdensitometry and then re-scale the average values every 14 days. Climatic variables for the monitoring period were obtained and grouped every 14 days. The effect of the climate variables was determined by maximum and minimum growth periods in assessing trunk growth. These growth periods were related with precipitation, average temperature and relative air humidity. The re-scaled wood density values, calculated using the radial growth of the tree trunks measured accurately with steel dendrometers, enabled the determination of the relationship of small changes in wood density and the effect of the climatic variations and growth rate of eucalyptus tree trunks. A high sensitivity of the wood density to variation in precipitation levels was found.

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.

Application of fuzzy logic for the evaluation of livestock slaughtering

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.

Method of numerical correction of errors occasioned by delay of records during the monitoring of environmental variables of interest for animal production

Thermal and air conditions inside animal facilities change during the day due to the influence of the external environment. For statistical and geostatistical analyses to be representative, a large number of points spatially distributed in the facility area must be monitored. This work suggests that the time variation of environmental variables of interest for animal production, monitored within animal facility, can be modeled accurately from discrete-time records. The aim of this study was to develop a numerical method to correct the temporal variations of these environmental variables, transforming the data so that such observations are independent of the time spent during the measurement. The proposed method approached values recorded with time delays to those expected at the exact moment of interest, if the data were measured simultaneously at the moment at all points distributed spatially. The correction model for numerical environmental variables was validated for environmental air temperature parameter, and the values corrected by the method did not differ by Tukey's test at 5% significance of real values recorded by data loggers.